Fingerprint classification using an AM-FM model

Research on fingerprint classification has primarily focused on finding improved classifiers, image and feature enhancement, and less on the development of novel fingerprint representations. Using an AM-FM representation for each fingerprint, we obtain significant gains in classification performance...

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Bibliographic Details
Published inIEEE transactions on image processing Vol. 10; no. 6; pp. 951 - 954
Main Authors Pattichis, M.S., Panayi, G., Bovik, A.C., Shun-Pin Hsu
Format Journal Article
LanguageEnglish
Published New York, NY IEEE 01.06.2001
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Applied sciences
Artificial intelligence
Biological system modeling
Classification
Classifiers
Computer networks
Computer science; control theory; systems
Exact sciences and technology
Fingerprint recognition
Fingerprints
Frequency modulation
Gain
Image databases
Image matching
Image processing
Information, signal and communications theory
Multidimensional systems
Neural networks
NIST
Pattern recognition. Digital image processing. Computational geometry
Performance gain
Representations
Signal processing
Telecommunications and information theory
Frequency modulation
Neural network
Image processing
Classification
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Summary:Research on fingerprint classification has primarily focused on finding improved classifiers, image and feature enhancement, and less on the development of novel fingerprint representations. Using an AM-FM representation for each fingerprint, we obtain significant gains in classification performance as compared to the commonly used National Institute of Standards system, for the same classifier.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:1057-7149
1941-0042
DOI:10.1109/83.923291